Real-world evaluation of care for type 2 diabetes in Malaysia: A cross-sectional analysis of the treatment adherence to guideline evaluation in type 2 diabetes (TARGET-T2D) study

Aim Given a lack of data on diabetes care performance in Malaysia, we conducted a cross-sectional study to understand the clinical characteristics, control of cardiometabolic risk factors, and patterns of use of guideline-directed medical therapy (GDMT) among patients with type 2 diabetes (T2D), who were managed at publicly-funded hospitals between December 2021 and June 2022. Methods Patients aged ≥18 years with T2D from eight publicly-funded hospitals in the Greater Kuala Lumpur region, who had ≥2 outpatient visits within the preceding year and irrespective of treatment regimen, were eligible. The primary outcome was ≥2 treatment target attainment (defined as either HbA1c <7.0%, blood pressure [BP] <130/80 mmHg, or low-density lipoprotein cholesterol [LDL-C] <1.8 mmol/L). The secondary outcomes were the individual treatment target, a combination of all three treatment targets, and patterns of GDMT use. To assess for potential heterogeneity of study findings, all outcomes were stratified according to prespecified baseline characteristics namely 1) history of atherosclerotic cardiovascular disease (ASCVD; yes/no) and 2) clinic type (Diabetes specialist versus General medicine). Results Among 5094 patients (mean±SD age 59.0±13.2 years; T2D duration 14.8±9.2 years; HbA1c 8.2±1.9% (66±21 mmol/mol); BMI 29.6±6.2 kg/m2; 45.6% men), 99% were at high/very high cardiorenal risk. Attainment of ≥2 treatment targets was at 18%, being higher in General medicine than in Diabetes specialist clinics (20.8% versus 17.5%; p = 0.039). The overall statin coverage was 90%. More patients with prior ASCVD attained LDL-C <1.4 mmol/L than those without (13.5% versus 8.4%; p<0.001). Use of sodium-glucose cotransporter-2 (SGLT2) inhibitors (13.2% versus 43.2%), glucagon-like peptide-1 receptor agonists (GLP1-RAs) (1.0% versus 6.2%), and insulin (27.7% versus 58.1%) were lower in General medicine than in Diabetes specialist clinics. Conclusions Among high-risk patients with T2D, treatment target attainment and use of GDMT were suboptimal.


Introduction
Type 2 diabetes (T2D) is one of the major public health concerns in Malaysia.Based on the Malaysian National Health and Morbidity Survey in 2019, the prevalence of diabetes in adults aged �18 years has increased from 11.2% in 2011 to 18.3% [1].This brings the total number of adults living with diabetes to 3.9 million [1].Key cardiometabolic risk factors namely T2D, hypertension, and dyslipidaemia often occur together.To date, 3.4 million patients have two or more of these risk factors [1].This highlights the importance of multicomponent interventions in managing patients with T2D to mitigate the long-term risk of complications and improve quality of life [2].
The increasing burden of T2D and its complications imposes substantial healthcare costs (both direct and indirect), especially when the healthcare system is heavily subsidized by the Malaysian government [3,4].Although atherosclerotic cardiovascular disease (ASCVD) and heart failure are leading causes of disability and premature death, the 2019 GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Study reported the lack of improvement in mitigating these risks on a global level in the past three decades [5].High systolic BP, high low-density lipoprotein cholesterol (LDL-C), high body mass index (BMI), high fasting plasma glucose, and kidney dysfunction remain the top five modifiable risk factors for ASCVD and heart failure between 1990 and 2019 [5].
Given its high burden and the paradigm shift in T2D management, evidence-based consensus guidance and new quality indicators have been developed for increasing the efficiency of care delivery.In Malaysia, the National Diabetes Registry was established in 2009 to evaluate the variations in care delivery and to uncover opportunities for quality improvement at publicly-funded primary care clinics [25].However, similar mechanisms in hospital-based settings have thus far been limited.

Study design and population
The TARGET-T2D study is the first, large-scale quality improvement initiative for understanding the care patterns of patients with T2D in hospital-based settings in Malaysia.This was a cross-sectional study to describe the clinical characteristics, control of cardiometabolic risk factors, and patterns of medication use at eight publicly-funded specialist hospitals in the Greater Kuala Lumpur region, the capital of Malaysia.Three hospitals were academic institutions under the Ministry of Higher Education (MOHE) whilst the remaining hospitals were managed by the Ministry of Health (MOH) (Fig 1).We included patients aged �18 years with T2D treated with oral glucose-lowering drugs and/or injectable therapy, who had at least two outpatient visits at either Diabetes specialist or General medicine clinics within the preceding year of data collection.We excluded patients with 1) type 1 diabetes, defined as a presentation with either diabetic ketoacidosis, unprovoked ketosis, or continuous insulin requirement within 12 months of diagnosis; 2) gestational diabetes mellitus, and 3) secondary diabetes mellitus.
We used the convenience sampling method and conducted data collection at all study sites from 13 December 2021 to 30 June 2022 for a total duration of six months.Before each clinic day, the study team prepared the outpatient appointment lists to facilitate data collection.The study team was trained to extract relevant data (including sociodemographic, comorbidities, medications, anthropometric, and laboratory measurements) from health records (either electronic or manual, depending on the site facility).We standardized data collection using established definitions, uniform data entry, and periodic data quality assurance by the Steering Committee of the study.We developed a TARGET-T2D web portal in collaboration with the Department of Software Engineering, University of Malaya.All data were pseudonymized and stored in the web portal in a manner compliant with local regulations.Any data not meeting predefined clinical plausibility thresholds were flagged for manual review with each study site.
The present study was approved by the Medical Research & Ethics Committee, Ministry of Health (NMRR ID-21-02100-BPE [IIR]) and three MOHE institutional ethics review boards.Given that there was no data collection beyond that of routine care, a waiver of written informed consent was granted.

Study outcomes
The primary outcome was the proportion of patients with T2D attaining �2 treatment targets, defined as 1) HbA 1c <7.0% (53 mmol/mol); 2) BP <130/80 mmHg; and 3) LDL-C <1.8 mmol/L [23,[26][27][28].Secondary outcomes were the individual target, a combination of all three targets, and medication patterns.To assess for potential heterogeneity of results, all study outcomes were stratified according to prespecified baseline characteristics namely prior ASCVD and clinic type (Diabetes specialist versus General medicine).
Based on the recommendations of the Malaysian Clinical Practice Guideline of Type 2 Diabetes [23], we recorded glycaemic parameters namely fasting plasma glucose and HbA 1c that were available up to six months prior to data collection.For non-glycaemic parameters namely lipid profile (including total cholesterol, LDL-C, triglyceride, and high-density lipoprotein cholesterol [HDL-C]), kidney function, liver function, and albuminuria, we recorded these measurements up to 12 months prior to data collection.To standardize the definition of albuminuria, we converted the values of urinary protein:creatinine ratio to urinary albumin:creatinine ratio (ACR) based on the equation developed by the CKD Prognosis Consortium [29].We used the most recent laboratory measurements to define study outcomes.

Statistical analysis
Data were presented as mean±standard deviation (SD) or median (interquartile range [IQR]) for continuous variables with either normal or skewed distribution, respectively.We assessed for normality of data using the histograms, QQ plots, Shapiro Wilk, or Kolmogorov Smirnov test.We logarithmically transformed continuous variables with skewed distributions for analysis.Categorical variables were presented as numbers and percentages.Patients with T2D were categorized into either moderate, high, or very high cardiovascular risk based on the 2019 European Society of Cardiology (ESC) risk criteria [26].
For the two-group comparison of continuous variables, we used an independent t-test for data with normal distributions whilst Wilcoxon rank-sum test was for data with skewed distributions.We used the Chi-square test for between-group comparisons of categorical variables.We performed subgroup analyses, stratified by history of ASCVD and clinic type (Diabetes specialist versus General medicine).
We performed pairwise deletion for variables with missing values.All analyses were performed using R 4.2.1 [30].A 2-tailed p-value <0.05 denoted statistical significance.

Results
Fig 1 describes the study flow.Among 5102 patients with T2D, we included 5094 patients aged �18 years in the present analysis, of whom 45.6% were men.Table 1 shows the baseline characteristics of the overall cohort, stratified by ASCVD status.The cohort was predominantly of Malay ethnicity (58.2%), followed by Indian (23.6%) and Chinese (18.2%).Fewer than 10% of them were current smokers.

Discussion
In this real-world cohort of >5000 patients with T2D from eight urban, publicly-funded, hospital-based clinics, we highlighted several findings in relation to the cardiometabolic risk profiles and quality of care.More than 90% of the cohort were either high-or very high-risk for cardiorenal diseases, showing no significant difference between the Diabetes specialist and General medicine clinics.The present cohort also had high rates of general and central obesity, especially in women with T2D.Of note, one in five patients attained �2 treatment targets (HbA 1c <7% (53 mmol/mol), BP<130/80 mmHg, and LDL-C<1.8 mmol/L), showing a higher proportion among those either with prior ASCVD or managed in the General medicine clinics.Although statin coverage was >90%, there was suboptimal attainment of LDL-C targets even among patients with prior ASCVD, wherein fewer than 15% of them attained LDL-C<1.4 mmol/L.Despite having a high proportion of at-risk patients, use of newer guideline-directed medical therapy (GDMT) such as SGLT2 inhibitors and GLP1-RAs was suboptimal, especially among those managed in the General medicine clinics.
Compared with previous hospital-based studies that were conducted in 2008 and 2013, the control of glycaemia among patients with T2D in the present study has modestly improved [31,32].About one-third of the present cohort attained HbA 1c <7% (53 mmol/mol), which was consistent with T2D populations in other middle-income countries such as China and India [33].However, this was lower than what had been reported in high-income countries, which ranged between 45% and 80% [33].The selection of HbA 1c <7% (53 mmol/mol) as a treatment target in the present study could be debated.This target was based on the 2022 American Diabetes Association Standard of Medical Care [27] and our local guideline [23].In real-world practice, the HbA 1c target can be individualized between 7% (53 mmol/mol) and 8.5% (69 mmol/mol) according to the patient's age, comorbidities, and hypoglycaemia risk [27,34].On the other hand, therapeutic inertia could contribute to suboptimal control of glycaemia.In a retrospective analysis of the Malaysian primary care-based National Diabetes Registry, among non-insulin-treated patients with T2D and HbA 1c �8% (64 mmol/mol), 54% had delayed treatment intensification with a median time of 13 months [35].
Obesity, hypertension, and dyslipidaemia can interact with hyperglycaemia in the development and progression of cardiorenal diseases, cancer, and other microvascular complications [2].In the present cohort, three-quarters had general obesity with a mean BMI of 30 kg/m 2   and >90% of women had central obesity.These findings were consistent with a multinational CAPTURE study which involved a predominantly White population [36].According to the 2019 population-based Malaysian National Health and Morbidity Survey, 50% of adults had a BMI of �25 kg/m 2 , being more common in women than in men [1].Indeed, the mean BMI among patients with T2D has increased from 28 kg/m 2 in DiabCare 2008 [31] to 29 kg/m 2 in DiabCare 2013 [32], and 30 kg/m 2 in the present cohort.
Achieving hypertension control has been challenging wherein only 23% of the present cohort reported having BP <130/80 mmHg.Although the presence of multiple comorbidities among patients at hospital-based clinics was common and could be associated with suboptimal control, the proportion of patients at primary care clinics attaining BP �135/75 mmHg, who tended to have fewer comorbidities, was similar at 26% [37].One possibility was white-coat hypertension as clinic BP, but not home BP, was recorded.Other potential reasons include the lack of disease awareness, infrequent home BP monitoring, and suboptimal treatment adherence due to polypharmacy, medication side effects, and self-care behaviour [2,38].In addition, salt intake is an important determinant of BP.Alarmingly, 79% of adults in Malaysia reported consuming >5 grams (1 teaspoon) daily, which was beyond the recommended intake by the World Health Organization [39].We report that one in four high-and very high-risk patients had adequate control of LDL-C level (<1.8 mmol/L), which is consistent with other Asian countries/regions.In a large retrospective cohort of >100,000 high-risk patients with diabetes in Korea, the mean LDL-C level was 2.9 mmol/L and 12% attained LDL-C <1.8 mmol/L [40].In a multinational SUrvey of Risk Factors (SURF) study, the proportion of high-risk patients attaining LDL-C <1.8 mmol/L was 15% in China and Taiwan, compared with 33% and 35% in European and Middle-Eastern countries [41].Future analysis by the type and dose of statin therapy (high-versus moderate intensity), as well as the different combinations of lipid-lowering therapy, may provide insights on how to close these gaps in care.The lack of patient-provider communication on the safety of statin therapy such as muscle symptoms, may also affect patient treatment adherence [42].In a meta-analysis of 19 randomized clinical trials, statin therapy was associated with an absolute excess rate of 6-16 events per 1000 person-years of muscle symptoms during year 1 [43].There was no significant excess risk during subsequent years [43].Indeed, 90% of all reports of muscle symptoms among statin-treated patients were not due to statin therapy [43].Apart from the aforementioned patient-level factors, the lack of a reliable cardiovascular risk stratification tool and therapeutic inertia could be associated with suboptimal risk-based LDL-C management [44].
Our findings indicate that one-third of the present high-risk cohort were treated with SGLT2 inhibitors, with a much lower proportion of 13% in General medicine clinics.The latter is consistent with other reports with similar time periods from the US [45] and the CAP-TURE study [36].Use of GLP1-RAs was only 4% among patients with ASCVD, reflecting the lack of availability of this class of GDMT.The uptake of these GDMT may change with the recent updates to consensus guidance that now recommend an SGLT2 inhibitor or GLP1-RA as first or second-line treatment in patients with either high-risk T2D or cardiorenal diseases https://doi.org/10.1371/journal.pone.0296298.g003[23,24,34,46].The influence of these consensus updates on real-world practice is of interest and hence, the present study provides a benchmark for quality improvement.On the other hand, access and availability of SGLT2 inhibitors and GLP1-RAs depend on the purchasing decisions, medication quota, and prescribing rights in individual publicly-funded hospitals.For instance, at the time of the TARGET-T2D study, SGLT2 inhibitors were not approved for use at General medicine clinics and hence, patients who were indicated for treatment would need to be referred to Endocrinologists.
The major strength of the present study is the shared protocol for standardized data collection and quality assurance at eight publicly-funded tertiary care hospitals.In addition, use of a structured care record form, established data definitions, and an electronic data capture system with quality control may be key measures for periodic performance tracking and identification of gaps in care [2].Importantly, our hospital-based data will complement the findings from the National Diabetes Registry which involves publicly-funded primary care clinics.Taken together, we are hopeful that our data will offer an impetus for the improvement of care standards over time among patients with T2D in Malaysia.
We acknowledge several study limitations.First, due to the pragmatic nature of the present study, there was potential selection bias due to the enthusiasm of participating study sites.Patients who were younger, with shorter disease duration, and less complex diseases might be under-represented, biasing our findings to those with more severe disease.Second, given that all study sites were urban publicly-funded hospitals in the Greater Kuala Lumpur region, there is limited generalizability to patients with T2D living in rural areas, patients managed in private healthcare facilities, and on a nationwide level.Last, given that not all study sites had electronic health records systems and manual data extraction was necessary, we limited the number of data collected in the real-world practice by excluding questionnaires on hypoglycaemia risk and patient-reported outcomes.
In conclusion, compared with previous audits (although with different hospital-based patient groups), we have reported modest improvement in cardiometabolic risk factors and treatment target attainment in the public hospital setting.Given finite resources, our data highlight potential gaps in care which can facilitate effective resource allocation.To address the epidemic of T2D in Malaysia, the present TARGET-T2D study is well-positioned to enable future data collection on a nationwide level, monitoring of trends, and longitudinal evaluation of health outcomes.